Parallel Computing with Python

Understanding how to distribute your code across several compute nodes is the first step toward solving problems more efficiently or making larger problems tractable. Python has very accessible tools that make running your code in parallel straightforward. In this tutorial we’ll look at how multiprocessing and IPython parallel can be used to solve problems that are naturally independent. This includes applications in image processing, parameter optimization, and machine learning. 

Please bring a laptop if you are interested in test driving a few of the examples.  I will have a multi-core Amazon Web Service EC2 instance running a notebook for everyone that signs up.

Hope to see you there.


We will be meeting in the TLC, room 215. The best place to park if you are driving is at the Euclid AutoPark. 

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  • Larry R.

    Excellent tour of the parallel choices available. Well prepared, well done. Having the AWS instances available to follow along and experiment added a lot.

    April 24, 2014

  • Michael G.

    Super useful for me! Thanks!

    April 24, 2014

  • Larry R.

    Are we still in TLC 215 for the rescheduled date?

    April 16, 2014

    • Monte L.

      Yes, same time and place. Thanks for clarifying. See you next week Larry.

      April 17, 2014

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